• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.183-186
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• 2000

영상 분할(image segmentation)은 주어진 영역에서 의미 있는 영역만을 분리해 내는 과정으로 컴퓨터 비젼 분야에 있어 매우 중요한 단계로 취급되어 진다. 본 연구에서는 기존의 영상 분할 알고리즘들의 문제점을 해결하고자 단계적인 marker 영상을 적용한 watershed 알고리즘을 제안하였다. 제안한 방법은 단계적인 level의 조절에 따라 분할의 정도를 선택할 수 있으며 watershed 알고리즘의 특성인 정확한 물체 검출의 장점들 살릴 수 있다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.225-230
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• 2011

In this paper, we propose the segmentation method for detecting the facial region by using watershed based on depth information and merge algorithm. The method consists of three steps: watershed segmentation, seed region detection, and merge. The input color image is segmented into the small uniform regions by watershed. The facial region can be detected by merging the uniform regions with chromaticity and edge constraints. The problem in the existing method using only chromaticity or edge can solved by the proposed method. The computer simulation is performed to evaluate the performance of the proposed method. The simulation results shows that the proposed method is superior to segmentation facial region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.409-415
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• 2017

This paper proposes a road segmentation algorithm using a watershed. The proposed algorithm is a segmentation algorithm using an automatic marked watershed that automatically creates a road marker and a background marker using information about vehicles and lanes on road and it can solve problems of a watershed-based segmentation such as overmany regions or handworks for markers. The road marker has property for pure road areas in which lanes are included but vehicles are excluded and the background marker has property for the areas left in which vehicles and background are included. Results of segmentation applied to real road images show that the proposed algorithm can automatically creates appropriate markers and it can properly segments the required road area that include the lane with a vehicle and its both side lanes in various environments, and it is equal to the conventional algorithm using markers created by handwork in performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.113-119
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• 2001

In this paper, we propose an improved watershed algorithm that resolves the oversegmentation problem shown in the previous watershed algorithm and its modifications when the spatial video segmentation is performed. The principal idea of the proposed algorithm is merging the shallow catchment basin whose depth is less than a given threshold into the deeper one during flooding step. In the flooding process, the growth of the existing catchment basins and the extraction of newly flooded ones are accomplished. We present the experimental results using several MPEG test sequences in the last part of the paper. As a consequence, the proposed algorithm shows good segmentation results according to the thresholds applied by adding very small amount of calculations.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.4
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• pp.3-12
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• 2006

Watershed is the land area that contributes runoff to an outlet point. To delineate an watershed, watershed delineation using GIS that contains grid data structure is the most general method. Some researchers have studied to implement algorithms that revise the TIN topography since it is difficult to delineate watershed boundary more accurately. In this study kruskal's greedy algorithm and triangulated irregular network (TIN) were used to delineate a watershed. This method does not require a conversion from to DEM in grid and automatically obtain(generates) the oulet points. Delineation algorithm was tested in Geosan-gun, Chung-cheongbuk-do and get small watershed areas. Finally, kruskal's algorithm could operate more precisely with revision algorithm.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.709-721
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• 2009

This paper discusses an efficient image segmentation using morphological watershed algorithm that is robust to noise. Morphological image segmentation consists of four steps: image simplification, computation of gradient image and watershed algorithm and region merging. Conventional watershed segmentation exhibits a serious weakness for over-segmentation of images. In this paper we present a morphological edge detection methods for detecting edges under noisy condition and apply our watershed algorithm to the resulting gradient images and merge regions using Kolmogorov-Smirnov test for eliminating irrelevant regions in the resulting segmented images. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with percentage error as well as computational time needed to segment images. The proposed algorithm can efficiently improve segmentation accuracy and significantly reduce the speed of computational time.

• Journal of the Korea Computer Industry Society
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• v.3 no.5
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• pp.575-584
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• 2002

On-line handwritten character recognition be achieved successful results since effectively neural networks divided the letter which is the time ordering of strokes and stroke position. But off-line handwritten character recognition is in difficulty of incomplete preprocessing because has not information of motion or time and has frequently overlap of the letter and many noise occurrence. consequently off-line handwritten character recognition needs study of various methods. This paper apply watershed algorithm to preprocessing for off-line handwritten hangul character recognition. This paper presents effective method in four steps in watershed algorithm as consider execution time of watershed algorithm and quality of result image. As apply watershed algorithm with effective structure to preprocessing, can get to the good result of image enhancement and binarization. In this experiment, this paper is estimate the previous method with this paper method for execution time and quality in image. Average execution time on the previous method is 2.16 second and Average execution time on this paper method is 1.72 second. While this paper method is remove noise effectively with overlap stroke, the previous method does not seem to be remove noise effectively with overlap stroke.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.71-74
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• 2012

본 논문에서는 새로운 문자 분할 알고리즘을 제안한다. 고전적인 문자 분할 알고리즘은 학술적인 문서영상과 같이 단순한 구조를 가진 문서영상을 대상으로 하여 좋은 성능을 보였지만 다양한 문자 크기와 색상, 그림, 복잡한 배경 등으로 구성된 문서영상에서는 좋지 못한 성능을 보인다. 최근에 제안고 있는 방법들은 복잡한 문서영상에서도 좋은 성능을 보이도록 다양한 기법들을 적용하여 우수한 성능을 보이고 있지만, 대부분의 방법들이 영상을 일정한 크기의 블록으로 나누어 문자분할을 하기 때문에 세밀한 부분에서는 성능이 어느 정도 한계를 보인다. 따라서 본 논문에서는 블록의 크기에 제한을 갖지 않는 새로운 방법으로서, watershed 알고리즘을 이용한 문자분할 방법을 제시한다. 구체적으로, watershed 알고리즘을 이용하여 문서영상의 구조(docstrum)를 파악하고 이를 기반으로 문자를 분할한다. 제안하는 방법은 크게 엣지 검출, distance transform, watershed 알고리즘을 이용한 docstrum 분석, 문자 분할의 네 단계를 거친다. 실험 결과 블록에 기반한 기존의 방법들이 놓치는 세밀한 부분에서도 제안된 알고리즘은 올바른 분할결과를 얻을 수 있음을 확인하였다.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1463-1473
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• 2010

In this paper, we propose a modified watershed algorithm to extract more correct edge and reduce processing time. Two new algorithms are proposed in this paper. The first one is applying two conventional watershed expansion methods known as rainfall and immersion simulation jointly. We analyze the advantage and problem of each simulation and then propose a new expansion method that keeps the advantage and removes the problem in order to extract more correct edge and reduce processing time. The second is a new priority decision algorithm to obtain more correct edge of a region. Some zero-crossing points of gradient are expected to be edge of a region but the conventional method has a limitation that it cannot extract those points as edge. Therefore we propose a new priority decision algorithm for watershed in order to get more correct edge. We compare the proposed method with the conventional method through experiments and prove that the proposed method can extract more correct edge of region.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.224-227
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• 2004

본 논문은 최소점 검색과 레이블 할당 시에 임계치를 적용한 개선된 워터쉐드(watershed) 알고리즘을 제안한다. 기존의 워터쉐드 알고리즘은 과분할의 문제점을 발생시키며 그로 인한 후처리가 필요하다 이러한 과분할 영역은 특히 객체의 경계주위에서 발생하여 부정확한 영역의 경계를 만든다. 이러한 문제점들을 해결하기 위해서 본 논문에서는 과분할을 막기 위해 잡음 제거와 경사(gradient) 영상을 구해 영상을 단순화시킨 후, 최소점 검색과 레이블 할당 시에 임계치를 적용한 개선된 워터쉐드 알고리즘을 적용해 과분할을 억제하고 분할된 영역의 경계를 정확히 나타나도록 하였다.